Method And Apparatus For Cuff-Less Blood Pressure Measurement In A Mobile Device

ABSTRACT

A system and method is presented for cuff-less blood pressure measurement in a mobile device. A key aspect of this disclosure is the discovery of a new location for blood pressure measurement at the fingertip of a subject and that reflectance-mode photoplethysmography can be used to help make this measurement. Through experiments in human subjects, it was discovered that it is indeed possible to measure systemic blood pressure by having a subject press the fingertip against a reflectance-mode photo-plethysmography-force sensor unit under visual guidance and then compute blood pressure from the resulting variable-amplitude blood volume oscillations and applied pressure via an oscillometric algorithm.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/118,530 filed on Aug. 31, 2018; which is a continuation-in-part ofand claims the benefit of priority to International Application No.PCT/US2017/020739, filed Mar. 3, 2017, which in turn claims the benefitof U.S. Provisional Application No. 62/303,074, filed Mar. 3, 2016 andU.S. Provisional Application No. 62/436,477, filed Dec. 20, 2016. Thepresent application also claims the benefit of U.S. ProvisionalApplication No. 62/555,028, filed Sep. 6, 2017 and U.S. ProvisionalApplication No. 62/554,795 filed Sep. 6, 2017. The entire disclosures ofthe applications referenced above are incorporated by reference.

GOVERNMENT CLAUSE

This invention was made with government support under EB018818 awardedby the National Institutes of Health. The government has certain rightsin the invention.

FIELD

The present disclosure relates to a method of cuff-less blood pressuremeasurements in a mobile device.

BACKGROUND

Hypertension afflicts about one-fourth of the world's adult population.It is a major risk factor for stroke and heart disease and is thereforea “silent killer”. Hypertension can be treated with lifestyle changesand medication. Medical therapy is associated with a 35-40% reduction inthe risk of stroke and a 15-25% reduction in the risk of heart disease.Hence, hypertension management is an archetypical example of preventive,proactive healthcare. However, the detection of high blood pressure (BP)is often missed. An estimated 20% of people with hypertension in the USdo not know they have it. Further, BP in known hypertensive patients isoften uncontrolled. An estimated 53% of hypertensive patients in the USdo not have their BP under control. Hypertension detection and controlrates are much worse elsewhere, especially in low resource settingswherein personnel trained in BP measurement and the means for people tohave their BP measured are lacking. Hypertension management iscomplicated by the well-known masked and white coat effects in theclinic and large BP variability amongst few measurements. In fact,ambulatory BP monitoring is now considered the gold standard for thediagnosis of high BP. Ubiquitous BP monitoring technology could improvehypertension detection by providing serial, out-of-clinic measurementsin the mass population and could enhance hypertension control byproviding continual feedback to the individual patient.

Several methods are available for measuring BP. However, none of thesemethods offers ubiquitous BP monitoring capabilities.

Catheterization is the gold standard method. This method measures a BPwaveform by placing a strain gauge in fluid contact with blood. However,this method is invasive.

Auscultation is the standard clinical method. This method measuressystolic BP (SP) and diastolic BP (DP) by occluding an artery with acuff and detecting the Korotkoff sounds using a stethoscope andmanometer during cuff deflation. The first sound indicates theinitiation of turbulent flow and SP, while the fifth sound is silent andindicates the renewal of laminar flow and DP. The method is non-invasivebut requires a skilled operator. Further, due to safety and ecologicalconcerns, mercury manometers are being replaced with high maintenanceaneroid manometers.

Oscillometry is the most popular non-invasive and automatic method. Thismethod measures mean BP (MP), SP, and DP using an inflatable cuff with asensor to record the pressure inside it. The recorded cuff pressure notonly rises and falls with cuff inflation and deflation but also showstiny oscillations indicating the pulsatile blood volume in the artery.The amplitude of these oscillations varies with the cuff pressure, asthe arterial blood volume-transmural pressure relationship is nonlinear.Transmural pressure of an artery is defined as the internal pressure(i.e., BP) minus the external pressure (cuff pressure in this case). TheBP values are estimated from the oscillogram (i.e., the oscillationamplitudes versus the cuff pressure) using an algorithm (e.g.,fixed-ratios). However, automatic cuffs do not afford ubiquitous BPmonitoring capabilities. That is, people in low resource settings maynot have any access to such devices; others must go out of their way(e.g., to a pharmacy) to use these devices; and even people who own adevice cannot carry and use them outside their homes.

Volume clamping is a non-invasive and automatic method used in research.This method measures a finger BP waveform by using a cuff with aphotoplethysmography (PPG) sensor built-in to measure the blood volume.The blood volume at zero transmural pressure is estimated by slowlyvarying the cuff pressure. The cuff pressure is then continually variedto maintain this blood volume throughout the cardiac cycle via a fastservo-control system. The applied cuff pressure may thus equal BP.However, in addition to requiring a cuff, the method is prohibitivelyexpensive.

Tonometry is another research method. This method measures a BP waveformby pressing a manometer-tipped probe on an artery. The probe mustflatten or applanate the artery so that its wall tension isperpendicular to the probe. However, manual and automatic applanationhave proven difficult. As a result, while the method should not requireany calibration, the measured waveform has been routinely calibratedwith a cuff in practice. Furthermore, the method is likewise costly.

As a result, cuff-less BP monitoring technology is being widely pursued.Much of these efforts are based on the principle of pulse transit time(PTT). PTT is the time delay for the pressure wave to travel between twoarterial sites. An increase in BP causes the arteries to stiffen which,in turn, causes PTT to decline. So, PTT is often inversely correlatedwith BP in individual subjects. Further, PTT may be simply determinedfrom the relative timing between proximal and distal arterial waveforms.Hence, PTT carries the advantage of possibly offering passive BPmonitoring without using a cuff. However, this approach also has majordisadvantages. Firstly, PTT not only changes with BP but also smoothmuscle contraction (especially when measured in small arteries) andaging and disease (especially when measured in large arteries). Smoothmuscle contraction occurs acutely and thus severely limits the accuracyof the approach, whereas aging and disease are longer processes thatprevent PTT from being able to track chronic changes in BP such as thecommon development of isolated systolic hypertension due to large arterystiffening with aging. Secondly, the required calibration of PTT inunits of msec to BP in units of mmHg must either be population-based andthus error-prone or involve periodic use of a BP cuff and thus not trulycuff-less.

In sum, hypertension is a major cardiovascular risk factor that istreatable, yet high BP detection and control rates are unacceptably low.Ubiquitous BP monitoring technology could improve hypertensionmanagement, but oscillometric and other available non-invasive BPmeasurement devices employ an inflatable cuff and therefore do notafford such monitoring capabilities. While the PTT approach couldpotentially permit cuff-less and passive BP monitoring, its accuracywill be limited due to confounding physiology and the need forcalibration. Hence, there is a need in the art for a ubiquitous methodfor reliable, cuff-less measurement of BP.

This section provides background information related to the presentdisclosure, which is not necessarily prior art.

SUMMARY

A handheld mobile device that measures blood pressure is presented. Themobile device includes: a processor enclosed within a housing; a displayunit integrated into an exterior surface of the housing; and a sensingunit integrated into an exterior surface of the housing. The sensingunit is configured to measure blood pressure at a fingertip of a user.The sensing unit includes a reflectance-mode photo-plethysmography (PPG)sensor configured to measure blood volume oscillations and a pressuresensor configured to measure pressure applied by the fingertip. Anon-transitory computer-readable medium enclosed in the housing storesinstructions that, when executed by the processor, cause the processorto: measure pressure applied to the sensing unit by a fingertip of auser, measure blood volume oscillations in the fingertip while varyingpressure is being applied to the sensing unit by the fingertip, generatean oscillogram from the measured pressure and the measured blood volumeoscillations, where the oscillogram plots amplitude of blood volumeoscillations as a function of the measured pressure; calculate a bloodpressure value from the oscillogram, and present the blood pressurevalue on the display unit.

The mobile device may include a visual guide disposed on the exteriorsurface and arrange in relation to the sensing unit. In one embodiment,the visual guide is further defined as indicia for placement of thefingertip in relation to the sensing unit.

The sensing unit may take on different forms. For example, the PPGsensor may be implemented by a light emitting diode cooperativelyoperating with a photodetector. Alternatively, the PPG sensor may beimplemented as a camera. In some examples, the pressure sensor is placedon top of the PPG sensor as it relates the exterior surface of thehousing. In other examples, the sensing unit is disposed underneath thedisplay unit.

In one embodiment, blood pressure is determined by an applicationresiding on the mobile device. Instructions comprising the applicationmay further cause the processor to guide the user via the display unitto vary pressure being applied to the sensing unit while blood volumeoscillations are measured. Instructions comprising the application mayalso cause the processor to guide the user to hold the mobile device ata height aligned with heart of the user.

DRAWINGS

The drawings described herein are for illustrative purposes only ofselected embodiments and not all possible implementations, and are notintended to limit the scope of the present disclosure.

FIG. 1 is a diagram depicting an example embodiment of a mobile devicethat embodies cuff-less BP measurements;

FIGS. 2A-2C are diagrams depicting an embodiment of the cuff-less bloodmeasurement system on the mobile device;

FIG. 3 is a diagram depicting an example embodiment of a cuff-lesssystem in a mobile device that obtains BP measurements;

FIG. 4 is a flowchart depicting an example embodiment of a cuff-lesssystem in a mobile device that obtains BP measurements;

FIG. 5 is a diagram depicting an example embodiment of the sensing unit;

FIGS. 6A and 6B are an example embodiment of how BP is estimated using aStandard Fixed-Ratio Algorithm;

FIGS. 7A and 7B are diagrams depicting an example embodiment of how BPis estimated using a Patient-Specific Algorithm;

FIG. 8 is a diagram depicting a prototype system that was created totest the feasibility of the oscillometric finger pressing paradigm;

FIGS. 9A and 9B are graphs depicting the pressure applied to the sensingunit and the target pressure displayed when pressure is applied to thesensing unit as well as the oscillogram that is generated to determineBP;

FIG. 10 is a diagram depicting an index finger that exerts the pressureapplied to the sensing unit of the prototype system;

FIGS. 11A-11C are diagrams depicting results of testing a prototypesystem;

FIG. 12 is a diagram depicting an example embodiment of cuff-less BPmeasurement devices;

FIG. 13 is a diagram depicting an example PPG sensor on the sensingunit;

FIGS. 14A and 14B are diagrams depicting example embodiments of sensingunits coupled to an encasing of mobile devices;

FIG. 15 is a diagram depicting another embodiment of the cuff-less BPmeasurement system on the mobile device;

FIG. 16 is a diagram depicting another embodiment of the cuff-less BPmeasurement system;

FIGS. 17A-17C are diagrams depicting an embodiment of the cuff-less BPmeasurement system with finger placement indicators;

FIGS. 18A-18D are diagrams depicting an example position detectionsystem included in the cuff-less BP measurement system; and

FIG. 19 is a flowchart depicting the example position detection systemincluded in the cuff-less BP measurement system.

Corresponding reference numerals indicate corresponding parts throughoutthe several views of the drawings.

DETAILED DESCRIPTION

Example embodiments will now be described more fully with reference tothe accompanying drawings.

The present invention relates to a reliable method for cuff-less BPmonitoring via the oscillometric principle. In conventionaloscillometry, an inflatable cuff serves as both an actuator to vary theexternal pressure of an artery and a sensor to measure this pressure andthe resulting variable-amplitude blood volume oscillations in theartery. BP is then estimated from the oscillation amplitudes as afunction of the applied pressure (again, the “oscillogram”). The idea ofthis disclosure is to extend the oscillometric principle for cuff-lessmonitoring of BP using a smartphone, another mobile device (e.g., PDAs,laptops, tablets, and wearables), and/or possibly an encasing of amobile device. Note that smartphones, in particular, are readilyavailable even to those in low resource settings.

The user serves as the actuator by pressing her finger against themobile device held at heart level to steadily increase the externalpressure of the underlying artery. Such finger actuation may affordexternal pressure application similar to a cuff in that the artery willbe pressed against supporting bone. The mobile device provides visualguidance for proper finger actuation, measures the applied pressure andblood volume oscillations, and estimates BP from the oscillogram. Thisinvention could be implemented with a photoplethysmography (PPG) sensor,which measures pulsatile blood volume and a pressure sensor embedded ina smartphone encasing or within the phone itself. By having the userserve as the actuator, the requisite hardware is automaticallyminiaturized and greatly simplified. Note that the mobile device mayalso warn users of high BP, securely transmit the measured BP tocaregivers, and send text reminders to patients with uncontrolled BP totake their medications. In this way, a complete hypertension managementsystem would be available to many

FIG. 1 is a diagram depicting an example embodiment of a cuff-less BPmeasurement system. The mobile device 100 includes a display 104 and asensing unit 108. The display 104 may present graphics that depict, in asingle graph 112, a pressure applied 116 by a finger to the sensing unit108 over a target pressure 118 for the finger to exert, finger bloodvolume oscillations 120 from the sensing unit 108, as well as the SP, DPand MP of the user as indicated at 124 of the display. In an exampleembodiment, the user presses her fingertip against the sensing unit 108to steadily increase the external pressure of the underlying artery,while the sensing unit 108, which includes a photoplethysmography (PPG)sensor and a pressure sensor, detects and measures the blood volumeoscillations and the pressure applied 116 to the sensing unit 108. Usingthe measured blood volume oscillations 120 and the pressure applied 116to the sensing unit 108, the oscillogram (i.e., amplitude of bloodvolume oscillations as a function of applied pressure) is generated.From the oscillogram, the SP, DP, and MP of the user are determined andpresented, for example using a display of the device. In addition, thepressure applied 116 to the sensing unit 108 is displayed in the graph112, and the blood volume oscillations 120 are displayed. The mobiledevice 100 includes but is not limited to mobile phones, PDAs, laptops,tablets, and wearable devices (e.g., watches).

FIGS. 2A-2C are diagrams further depicting the embodiment of thecuff-less BP measurement system on the mobile device 100. The userserves as the actuator by pressing her finger against the mobile device100, on the sensing unit 108, held at heart level to steadily increasethe external pressure of the underlying artery. Finger actuation canafford external pressure application similar to a cuff in that theartery will be pressed against supporting bone.

The mobile device 100 provides visual guidance on the display 104 forproper finger actuation. That is, having the graph 112 of the pressureapplied 116 to the sensing unit 108 on the same graph 112 as the targetpressure 118 provides the user with visual feedback as to how muchpressure to exert. The sensing unit 108 also measures blood volumeoscillations 120 to generate an oscillogram 128, and BP is estimatedfrom the oscillogram 128. The pressure applied 116 to the sensing unit108 is graphed in relation to target pressure 118 to guide the user onthe need to apply increased pressure and when to apply increasedpressure. Graphing the pressure applied 116 to the sensing unit 108 inreal time over the target pressure 118 allows the user to attempt totrace the target pressure 118. By having the user serve as the actuator,the requisite hardware is automatically miniaturized and greatlysimplified. The SP, the DP, and the MP can be calculated from theoscillogram 128.

FIG. 3 is a diagram depicting an example embodiment of a cuff-lesssystem that obtains BP measurements that may be implemented in themobile device 100. The system includes a display 104, a sensing unit108, a computer processor 300 and a data store 304 (e.g., anon-transitory storage medium). The system further includes anoscillogram generator 308, a BP estimator 312, and a pressure guide 316,which are implemented, for example, as computer-executable instructionsresiding in the data store 304 and executed by the computer processor300.

The sensing unit 108 is operably coupled to the computer processor 300of the mobile device 100. The sensing unit 108 includes a PPG sensor320, a pressure sensor 324, and possibly a temperature sensor 326. Thetemperature sensor 326 is optional, and the BP measurements may beobtained without it. The PPG sensor 320 of the sensing unit 108 isoperably coupled to the oscillogram generator 308, and the pressuresensor 324 is operably coupled to the oscillogram generator 308 and thepressure guide 30. The sensing unit 108 is configured to communicate themeasured values of the PPG sensor 320 and the pressure sensor 324 to thecomputer processor 300 of the mobile device 100. An example embodimentof the sensing unit 108 is further described below in FIG. 5.

The oscillogram generator 308 is configured to generate an oscillogrambased on input from the PPG sensor 320 and input from the pressuresensor 324. In an example embodiment, an oscillogram is constructed byfirst taking a maximum value and a minimum value of each beat of theblood volume waveform that is detected and measured by the PPG sensor320. The maximum value and minimum value of each beat, as a function ofthe pressure applied 116 to the sensing unit 108 (obtained by thepressure sensor 324), are then median filtered to attenuate respiratoryand heart rate variability. Finally, the maximum value and minimum valueof each beat are linearly interpolated, and the difference between thetwo envelopes is taken as the oscillogram 128. Although not limitedthereto, the oscillogram generator 308 may generate an oscillogram 128using other known algorithms as would be understood by one having skillin the art.

In extending this algorithm of generating the oscillogram 128 usingfinger pressing instead of a cuff, issues of detecting beats in thepresence of artifact and connecting the extrema of valid beats, whichcan be separated by a wide range of the pressure applied 116 to thesensing unit 108, may be present. To overcome these issues, algorithmsthat first identify artifact in the blood volume waveform that exploitthe anticipated blood volume shape and then detect the maxima and minimaof the artifact-free beats can be implemented into the system. Advancedfiltering and splining algorithms, as well as parametric model (Gaussianfunctions) fitting, which may be more robust, can be used to connect theextrema of the clean beats.

To assess the validity of the oscillogram 128, various features such asthe number of artifact-free beats, the applied pressure range over whichthese beats extend, and the shape, width, and degree of symmetry of theoscillogram 128 may be analyzed to determine the validity of theoscillogram 128. An algorithm such as linear discriminant analysis maybe implemented to distinguish between valid and invalid oscillogramsbased on these features.

The BP estimator 312 is configured to determine the BP based on theoscillogram 128 generated by the oscillogram generator 308.Subsequently, the BP estimator 312 presents the BP value on the display104. Example algorithms that may be used in estimating BP are theStandard Fixed-Ratio Algorithm, the Fixed-Slope Algorithm, aPatient-Specific Algorithm, and other variations of these algorithms.These algorithms may also be combined in various manners to estimate BP.

In addition, an age-dependent scaling algorithm of finger SP may be usedto estimate brachial SP, since the ratio of finger SP to brachial SP maydecrease with age. Brachial BP may also be determined from model-basedtransfer functions. While using the model-based transfer functions wouldrequire an input of the finger BP waveform, the finger BP waveform maybe obtained using a Patient-Specific Algorithm. Some example embodimentsof algorithms that may be used in estimating the BP are furtherdescribed below in relation to FIGS. 6A-7B.

The pressure guide 316 may optionally be interfaced with the pressuresensor 324. In some embodiments, the pressure guide 316 scales thepressure applied to the pressure sensor 324 to a measure of pressureapplied 116 to the sensing unit 108 exerted on the PPG sensor 320. Thepressure guide 316 is also configured to present the estimated magnitudeof the pressure applied to the sensing unit 108 on the display 104. Bydisplaying the amount of pressure applied to the sensing unit 108 on thedisplay 104, the pressure guide 316 also provides the user with realtime feedback regarding the amount of pressure applied to the sensingunit 108 and the location of the finger relative to the sensing unit108, as described further below. Thus, the user can take correctiveaction based on the real-time feedback so that the target pressure 118can be applied to the sensing unit 108 for a predetermined period oftime. The pressure guide 316 also receives feedback from the temperaturesensor 326. The temperature sensor 326 measures a temperature of thefinger applying pressure 116 to the sensor unit 108. Under thecircumstance that the temperature of the finger is too low or possiblytoo high, the display provides feedback informing the user that thefinger temperature is outside of an acceptable range, which can affectthe results of the BP measurement system.

In an example embodiment, the oscillogram generator 308, BP estimator312, and the pressure guide 316 may be implemented on the mobile device100 as an application. The application can be used to guide the fingeractuation, inform the user of any adjustments required in the pressureapplied 116 to the sensing unit 108 or finger placement, graph fingerpressure and possibly the blood volume oscillations 120, and display thegraphs along with the SP, DP, and MP/BP. The application uses thedisplay 104 and processor of the mobile device. For example, theapplication provides visual feedback to guide the finger actuation bygraphing the pressure applied 116 to the sensing unit 108 over thetarget pressure 118. That is, the target pressure 118 may be a lineartarget rise or a pressure in step increments, which may yield moreartifact-robust oscillograms over certain time interval (e.g., at least15 sec). The pressure applied 116 to the sensing unit 108 issuperimposed as it is being recorded in real-time. Alternatively, adisplay of the pressure applied 116 to the sensing unit 108 as itevolves in real-time within a plotting window that tells the user toraise the pressure steadily to a high level (e.g., 150 mmHg) over fixedtime interval, but not in any preset way, may be used. A third option isto guide the finger actuation through a video game that requires theuser press at various pressures to accomplish the goals of the game. Inaddition or in another embodiment, audio feedback could be used to guidethe finger actuation.

Additionally, after the BP has been computed, the application maydetermine whether the BP is within an acceptable range. If the BP fallsoutside of the acceptable range, the application may instruct the userto repeat the BP measurement in order to ensure accuracy.

The application then displays the computed BP and other physiologicvariables, if available, or asks the user to repeat the procedure in theevent of an unsuccessful finger actuation. The application could alsoask the user to repeat the procedure even when the actuation is deemedsuccessful. For example, the application could average two similar BPmeasurements or the two closest BP measurements out of three totalmeasurements to reduce variability. The application may also alert theuser if the BP is too high or too low, securely transmit themeasurements to the cloud as well as the physician, and send textreminders to users with repeatedly high BP measurements to take theirmedications. The application may further allow the user to view theirhistory of BP measurements over time and integrate with other health andlifestyle applications on the mobile device 100 such as those that trackeating habits.

The data store 304 is interfaced with the BP estimator 312 and thepressure guide 316. The data store 304 is configured to store BP values(MP, DP, and SP) that have been determined by the BP estimator 312.Pressure values from the pressure sensor 324 and PPG values from the PPGsensor 320 may also be stored in the data store 304. This may be usefulfor a user who is interested in tracking and analyzing BP values over aperiod of time to determine whether lifestyle changes, dietary changes,and/or exercise routines are improving her BP and overall cardiovascularhealth. The data store 304 may also be configured to provide thecomputer processor 300 of the mobile device 100 with processor readableinstructions for the oscillogram generator 308, the pressure guide 316,and the BP estimator 312. As an example, the data store 304 may providethe computer processor 300 of the mobile device 100 with executableinstructions that allow it to generate an oscillogram 128 from the bloodvolume oscillations detected and measured by the PPG sensor 320 and thepressure applied 116 to the sensing unit 108 detected and measured inthe pressure sensor 324. The data store 304 may also provide thecomputer processor 300 of the mobile device 100 with executableinstructions to estimate BP based on the oscillogram 128 generated bythe oscillogram generator 308 and an algorithm that estimates BP basedon certain parameters of the oscillogram 128.

The display 104 may provide the user with real-time feedback regardingthe pressure applied 116 to the sensing unit 108 and the location of thefinger relative to the sensing unit 108. As an example, the system mayprovide the user visual feedback when the pressure applied 116 to thesensing unit 108 is below a target pressure 118. As another example, thesystem may provide the user visual feedback when the location of thefinger is not at a predefined optimal finger location that allows foroptimal oscillogram measurements. The predefined finger location may bedetermined by an initialization protocol, which occurs when the fingeractuation is attempted over a range of locations on the sensor, and thelocation that yields the largest oscillogram amplitude is selected asthe predefined optimal finger location. The predefined optimal fingerlocation may be located on the upper index finger above a transversepalmer arch artery of the subject.

To guide the user in increasing the pressure applied 116 to the sensingunit 108, the target pressure 118 may have a trajectory of a linearrise, a step increment, or a combination of a step increment and alinear rise shown on the display 104. In other embodiments, the targetpressure 118 may not be displayed. For example, the display 104 couldinclude the desired start and end pressures with the time interval toreach the end pressure.

FIG. 4 is a flowchart depicting an example embodiment of a cuff-lesssystem that obtains BP measurements. The flowchart depicts an example ofa determination of proper finger positioning and proper pressure applied116 as may be implemented by the pressure guide 316 of FIG. 3. First,the system is initialized at 204. During this stage, the mobile devicemay initialize the display and the sensing unit (i.e., opening anapplication on the mobile device 100 and/or turning on the sensing unit108) to measure the pressure applied 116 to the sensing unit 108, theblood volume oscillations 120 with the sensing unit 108, the oscillogram128, and the SP, DP, and MP/BP and display the measurements once theuser begins to apply pressure to the sensing unit 108. The mobile device100 may also, using information loaded in a data storage unit, load theuser's predefined optimal finger location data. The user data may beaccessed by the initialization protocol by inserting a username or IDand a password to load the user's predefined optimal finger locationdata.

Second, the system begins to detect the pressure applied 116 to thesensing unit 108 at 208. Next, the system provides the user withreal-time feedback. At 212 the system then determines whether thelocation of the finger relative to the sensor is proper, wherein theproper location is the predefined optimal finger location. If so, thenat 216 the system determines whether the user is applying the properamount of pressure, wherein the proper amount of pressure is the targetpressure 118. If so, the system proceeds to the next step.

If the location of the finger relative to the sensing unit 108 is notproper at 212, or if the amount of pressure is not proper at 216, thesystem, at 220, provides corrective feedback so that the user can eithercorrect the amount of pressure applied to the sensing unit 108 or adjusther finger positioning relative to the sensing unit 108. As an example,the feedback may instruct the user to either increase or decrease theamount of pressure applied so that the user can apply the targetpressure 118. As another example, the feedback may instruct the user toadjust the positioning of her finger so that the positioning of thefinger is at the predefined optimal finger location. Control thenproceeds to 208. The feedback may be visual, audio-based, or acombination of visual and audio-based feedback.

Once the target pressure 118 is met and proper finger positioning isachieved, the sensing unit 108 measures and graphs the blood volumeoscillations and the pressure applied 116 to the sensing unit 108 at224. The system then displays the BP to the user. The system determinesthe SP and DP based on the blood volume oscillations and the pressureapplied 116 to the sensing unit 108. Using the SP and DP, the systemestimates the MP/BP from the blood volume oscillations and the pressureapplied 116 to the sensing unit 108 using various BP estimationalgorithms. Depending on the determination method, the MP/BP may bedetermined first followed by the SP and DP. In any case, the mobiledevice 100 subsequently displays the MP/BP.

FIG. 5 is a diagram depicting an example embodiment of the sensing unit108. The sensing unit 108 includes a PPG sensor 320 and a pressuresensor 324, wherein the PPG sensor 320 and the pressure sensor 324 arecoupled to each other by an interface unit 328. The PPG sensor 320 andthe pressure sensor 324 may be coupled to the computer processor 300 ofthe mobile device 100, wherein the computer processor 300 of the mobiledevice 100 may subsequently determine the BP from the detected values ofthe PPG sensor 320 and the pressure sensor 324. The sensing unit 320surface may be flat or concave to facilitate finger positioning on thesensing unit 108.

In an example embodiment, the PPG sensor 320 is an infrared,reflectance-mode PPG sensor that measures blood volume oscillations fromthe arteries beneath the skin. The PPG sensor 320 may be configured in away such that the blood volume oscillations of a transverse palmer archartery, above the top knuckle of the index finger, can be accurately andefficiently recorded. An LED and a photodetector (referenced anddiscussed in FIG. 13) of the PPG sensor 320 may be positionedperpendicular to the transverse palmer arch artery, wherein the LED andthe photodetector are separated by a fixed distance. The fixed distancemay be chosen such that the blood volume oscillation amplitudes detectedand measured by the PPG sensor 320 are maximized.

In an example embodiment, the pressure sensor 324 is a thin-filmedcapacitive transducer. The transducer outputs the pressure applied 116to the sensing unit 108 in the normal direction. The pressure sensor 324may be configured to output a pressure between the range of 0 to 250mmHg at an output resolution of less than 0.1 mmHg. Other pressuresensors that are configured to output a force when the pressure applied116 to the sensing unit 108 may also be used instead of the thin-filmedcapacitive pressure sensor 324 described in this embodiment.

In an example embodiment, the interface unit 328 is a thin, rigidstructure 328A adhesively coupled to a foam material 328B. The rigidstructure of the interface unit 328A is coupled to the PPG sensor 320,while the foam material of the interface unit 328B is coupled to thepressure sensor 324. This interface unit 328 allows for the forceapplied to the PPG sensor 320 to be distributed uniformly to thepressure sensor 324.

Alternatively, a silicone layer or similar material may be used in placeof the foam material 328B. Other materials that may be used in place ofthe foam material 328B are materials that are configured to distributean applied force evenly over its respective area and acts as amechanical low-pass filter to mitigate the impact of any spurious fingerpressing.

A surface of the sensing unit 108 that receives the pressure applied 116to the sensing unit 108 from the user should have an area that isoptimized in order to allow for reliable BP estimation. For example, incertain embodiments, if the area of the surface is too large, thensubstantial force will be needed to achieve the target pressure 118. Ifthe area of the surface is too small, then modest variations in pressureapplied 116 to the sensing unit 108 will induce substantial pressurechanges. The area of the surface of the sensing unit 108 that receivesthe applied force from the subject should therefore be optimized toallow for the sensing unit 108 to measure and detect the pressureapplied 116 to the sensing unit 108 that achieves an optimal balancebetween these two considerations.

FIGS. 6A and 6B are an example embodiment of how BP is estimated using aStandard Fixed-Ratio Algorithm. As described above, the oscillogramgenerator 308 receives data from the PPG sensor 320 and the pressuresensor 324 (e.g., the pressure applied 116 as depicted in FIG. 6A at 332and 336) to generate an oscillogram.

FIG. 6A is a diagram depicting the pressure applied 116 to an artery. Acuff is placed around a patient's arm and inflated. The cuff is inflatedwhile secured around the patient's arm, shown in FIG. 6A where the cuffpressure is increasing rapidly 332. Once the cuff reaches a targetexternal pressure to the artery, the cuff slowly deflates 336. Whiledeflating 336, the cuff measures a blood volume value and externalpressure and constructs an oscillogram from the resulting variableamplitude blood volume oscillations shown in FIG. 6B. The mean BP (MP)340 is estimated as the pressure at which the oscillogram is at amaximum amplitude 340 (A_(M)). Then, an amplitude of the SP (A_(S)) 344and an amplitude of the (A_(D)) DP 348 are estimated as the pressure atwhich the oscillogram is a fixed, population based average ratio of itsmaximal value (A_(S)/A_(M) and A_(D)/A_(M)). The ratios in thisembodiment are fixed such that A_(S)/A_(M) and A_(D)/A_(M) are equal to0.55 and 0.85, respectively. While this method depicts measuring BPusing the cuff, this algorithm can be applied in a cuff-less system aswell, wherein finger pressure is used instead of cuff pressure.

However, since the Standard Fixed-Ratio Algorithm is population based,the algorithm may be less effective in accurately determining BP levelsfor those individuals who have BP not within a normal BP range. The BPestimation errors of the Standard Fixed-Ratio Algorithm may besignificant and may be impacted by the width of the arterial compliancecurve, which is the derivative of the blood volume transmural pressurerelationship with respect to transmural pressure. The accuracy of theStandard Fixed-Ratio Algorithm may also be affected by those who have ahigh pulse pressure (i.e., the difference between the SP and DP) due toartery stiffening, a common condition that occurs with aging anddisease.

FIGS. 7A-7B are diagrams depicting an example embodiment of how BP isestimated using a Patient-Specific Algorithm. The oscillograms depictedat 368, and 384 are produced by the oscillogram generator 308 describedin FIG. 3. The Patient-Specific Algorithm represents the oscillogram 128with a physiologic model and then estimates the patient-specific modelparameters, which include BP levels and reflect the width and otherfeatures of the arterial compliance curve by optimally fitting the modelto the oscillogram 128. Thus, accuracy can be maintained over a wide BPrange. Furthermore, by employing a physiologic model, the method can bemore robust to deviations in the oscillogram 128 caused by respirationand heart rate variability and thus be more repeatable and reliable.While this method depicts measuring BP using a cuff, this algorithm canbe applied in a cuff-less system as well, wherein finger pressure isused instead of cuff pressure.

In FIG. 7A, air volume versus cuff pressure is shown for two differenttypes of cuffs: a dura cuff 352 and a bladder cuff 356. From the nearlylinear relationship displayed in FIG. 7A, a cuff compliance or scalefactor k 360 is determined.

The first step of estimating BP using the Patient-Specific Algorithm isto represent the cuff pressure oscillation amplitude versus the cuffpressure function (i.e., the oscillogram) with a parametric model of thenonlinear brachial artery blood volume-transmural pressure relationship.This representation is demonstrated in the following equation 1:

$\underset{\underset{{Red}\mspace{14mu} {Envelope}\mspace{14mu} {Difference}}{}}{P_{c}^{oa}(t)} = {{\underset{\underset{k \cdot d}{}}{e}\left\{ \underset{\underset{{Nonlinear}\mspace{14mu} {relationship}\mspace{14mu} {at}\mspace{14mu} {systole}}{}}{1 + \left\lbrack {{b^{- 1}\left( {{SP} - {P_{c}(t)} - a} \right)} + {b\left( \frac{c - 1}{c + 1} \right)}^{1/c}} \right\rbrack^{- c}} \right\}^{- 1}} - {e\left\{ \underset{\underset{{Nonlinear}\mspace{14mu} {relationship}\mspace{14mu} {at}\mspace{14mu} {diastole}}{}}{1 + \left\lbrack {{b^{- 1}\left( {{DP} - {P_{c}(t)} - a} \right)} + {b\left( \frac{c - 1}{c + 1} \right)}^{1/c}} \right\rbrack^{- c}} \right\}^{- 1}}}$

The unknown parameters (a, b, c, and e) represent the SP, DP, andbrachial artery mechanics. In terms of the brachial artery compliancecurve (i.e., the derivative of the nonlinear relationship with respectto transmural pressure), parameter a represents the transmural pressureat which the curve is a maximum; parameters b and c denote the width ofthe curve and the extent of the asymmetry about its maximum; andparameter e indicates the amplitude of the curve. The parameter e isdetermined by the reciprocal of the cuff compliance, which isrepresented by scale factor k 360. The scale factor k 360 is assumed tobe constant as justified by experimental data. A blood volume 372 isdetermined based on (i) the nearly linear relationship of the cuffpressure and air volume 356, (ii) blood volume oscillations 364, and(ii) cuff pressure oscillations 368. The envelope differences of theblood volume 372 are equal to within scale factor k 360.

The second step of estimating BP using the Patient-Specific Algorithm isto estimate the model parameters including the SP and DP by fitting themodel to the oscillogram. The model parameters are estimated using thefollowing equation 2:

$\min\limits_{\{{a,b,c,e,{SP},{DP}}\}}{\sum\limits_{t \in_{Period}^{Deflation}}\left\lbrack {{P_{c}^{oa}(t)} - {e\left\{ {1 + \left\lbrack {b^{- 1}\left( {\left( {{SP} - {P_{c}(t)} - a} \right) + {b\left( \frac{c - 1}{c + 1} \right)}^{1/c}} \right)} \right\rbrack^{- c}} \right\}^{- 1}} + {e\left\{ {1 + \left\lbrack {b^{- 1}\left( {\left( {{DP} - {P_{c}(t)} - a} \right) + {b\left( \frac{c - 1}{c + 1} \right)}^{1/c}} \right)} \right\rbrack^{- c}} \right\}^{- 1}}} \right\rbrack^{2}}$

The first step and the second step yield estimates for SP and DP as wellas parameters a, b, c, and e, which characterize the underlying model ofthe nonlinear brachial artery blood-volume transmural pressurerelationship. The third and fourth step use the parameter estimates toultimately yield an estimate for the entire brachial BP waveform (Pb(t))and MP, as described next.

The third step of estimating BP using the Patient-Specific Algorithm,which is shown in FIG. 7B, is to construct the blood volume waveform towithin the scale factor k 360 using the parameter estimates (i.e., a, b,c, and e) and cuff pressure oscillations. Positive cuff pressureoscillations 376 are calculated by subtracting a lower cuff pressureoscillation envelope 380 from cuff pressure oscillations 384. Then, theblood volume waveform to within scale factor k 388 is calculated byadding a modeled arterial blood volume-transmural pressure relationshipat diastole to within scale factor k 392.

The fourth step of estimating BP using the Patient-Specific Algorithm isto construct the BP waveform using the blood volume waveform 388 viaroot finding. From the BP waveform, MP is computed as the time averageof the derived waveform. The following equation 3 illustrates how the BPwaveform and the MP are derived:

${k - {V_{a}(t)}} = {e\left\{ {1 + \left\lbrack {b^{- 1}\left( {\left( {{P_{a}(t)} - {P_{c}(t)} - a} \right) + {b\left( \frac{c - 1}{c + 1} \right)}^{1/c}} \right)} \right\rbrack^{- C}} \right\}^{- 1}}$

Further details regarding the Patient-Specific Algorithm may be found inU.S. Provisional Application No. 62/217,331 filed Sep. 11, 2015incorporated by reference in its entirety herein.

The oscillometric principles of an inflatable cuff as described in FIGS.6A-7B are applied to cuff-less BP monitoring as shown in a prototypesystem 394. FIG. 8 is a diagram depicting the prototype system 394 thatwas created to test the feasibility of the oscillometric finger pressingparadigm.

The prototype system 394 consists of a simple sensor unit interfaced toa computer, which provides a visual display, as shown in FIGS. 9A and9B, and runs standard algorithms to estimate BP.

The sensing unit includes the PPG sensor 320 and pressure transducers asthe pressure sensor 324 housed in a plastic enclosure. The PPG sensor320 is an LED and photodetector operating in reflectance-mode and at aninfrared wavelength (940 nm) to penetrate an artery beneath the skin.The PPG sensor 320 surface, which constitutes the finger pressing area,is a 10 mm diameter circle. The pressure sensor 324 (DigiTacts Sensors,Pressure Profiling Systems, USA) is a thin-filmed, 16×3 array ofcapacitive transducer elements (5 mm length squares). Each elementoutputs the pressure exerted on it in the normal direction and hasspecifications that are congruent with BP measurement (e.g., resolutionand range are <1 mmHg and >250 mmHg). The PPG sensor 320 is on top ofthe pressure sensor 324 with a rigid structure-foam sheet interfacebetween the two. This interface allows the force applied on the PPGsensor 320 (but not elsewhere on the enclosure) to reach the pressuresensor 324 and be uniformly distributed on the pressure sensor 324. Theapplied finger pressure is the total force measured by all of thesensing elements divided by the pressing area. The pressure sensor 324was calibrated as it resides in the sensing unit by placing high densityweights on the PPG sensor 320. The relationship between the measuredvoltage and known pressure was nearly linear over physiologic pressures.

FIGS. 9A and 9B are graphs depicting the pressure applied 116 to thesensing unit 108 and the target pressure 118 displayed when pressure isapplied to the sensing unit 108 as well as the blood volume oscillations120 that are also generated to determine BP. The sensing unit isconnected to the computer via a data acquisition system (NI USB6009,National Instruments, USA). The visual display, which is implementedusing the data acquisition system software (LabVIEW, NationalInstruments), guides the user in performing the finger actuation. Theguidance is simply a display of the applied finger pressure 116 as itevolves in real-time within a plotting window that tells the user toraise the pressure steadily to 150 mmHg over a 30-sec interval but notin any preset way (e.g., a linear rise). The display also illustratesthe blood volume oscillations 120 as it is being measured and estimatedBP levels. Standard algorithms, which are implemented using computingsoftware (MATLAB, Mathworks, USA), are applied to the measured fingerpressure 116 and the blood volume oscillations 120 to construct anoscillogram 128 and estimate finger BP. In particular, BP is estimatedusing the fixed-ratio algorithm with the ratios set to typical values of0.85 for DP and 0.55 for SP.

FIG. 10 is a diagram depicting an index finger that exerts the pressureapplied 116 to the prototype system 394. The finger pressing protocolincludes pressing the PPG sensor 320 with the center of the indexfinger, shown in FIG. 10, above the top knuckle 396, which is above thetransverse palmer arch artery 400. The protocol further includesinstructing the user to apply the force in the normal direction whilethe finger is at heart level in order to eliminate confoundinghydrostatic effects. As previously described, the user may follow thefinger pressing protocol through the display 104 of the mobile device100 using an application to display the necessary graphs and prompts onthe display 104. When measuring the BP of the index finger, the traversepalmer arch artery 400 is the target artery, as discussed below.

FIGS. 11A-11C are diagrams depicting the results of the prototype system394. This basic prototype system 394 was studied in human subjects inthe seated posture (similar to cuff BP measurements) under IRB approval.Each subject addressed the sensing unit placed on a table at heart levelto eliminate hydrostatic effects. The subject placed the center of herindex finger above the top knuckle 396 on the center of the PPG sensor320. In this way, BP from the transverse palmer arch artery 400 would betargeted for measurement. The subject also rested a portion of herfinger below the top knuckle 396 on the sensing unit enclosure to ensurenormal direction force application. The subject then performed thefinger actuation under visual guidance. Many people, including those intheir 60's, could easily implement the finger actuation on the first tryor after one or two practice trials.

The cuff-less BP estimates of the system were compared to BPmeasurements from an oscillometric arm cuff device (BP760, Omron) in 23mostly inexperienced students and staff at Michigan State University(MSU). Each subject was allowed to practice the finger actuation acouple of times before recording the BP estimates. FIGS. 11A-11C depictcuff-less BP estimates versus the cuff measurements. FIG. 11A depictsthe cuff-less DP versus the cuff DP 404. FIG. 11B depicts the cuff-lessMP versus the cuff MP 408. FIG. 11C depicts the cuff-less SP versus thecuff SP 412. The bias and precision errors were about 1-3 and 7-11 mmHg.Since finger SP is larger than brachial SP, a crude estimate of brachialSP via a basic formula (SP=2.5*MP−1.5*DP) was instead used here.

FIG. 12 is a diagram depicting an example embodiment of cuff-less BPmeasurement devices. FIG. 12 depicts the measurement system included ina computer 500 and a watch 504. The computer 500 and the watch 504include the sensing unit 108 and the display 104 as shown in FIG. 1.

FIG. 13 is a diagram depicting an example PPG sensor 320 on the sensingunit 108. To measure the blood volume oscillations, any available sensorknown in the art may be employed. As shown in FIG. 13, the PPG sensor320, which is implemented in pulse oximeters, is used. Thereflectance-mode PPG sensor, in particular, may be congruent with mostform factors. The green wavelength, which typically yields a high ACsignal relative to the DC signal, or a near infrared wavelength, whichpenetrates beneath the skin, or multiple wavelengths (e.g., red andinfrared to also permit measurement of arterial oxygen saturation (402))may be employed.

A single photodetector 508 and light emitting diode 512 (LED) pair maybe used for measurement of blood volume in a target artery 516 such asthe transverse palmer arch artery 400 above the top knuckle 396 of anindex finger (see FIG. 10). The distance between the LED 512 andphotodetector 508 may be a few (e.g., 2) millimeters and positioned invarious ways including on a line perpendicular to the flow of arterialblood, as shown in FIG. 13. The arrows of the target artery 516 depictthe arterial blood flow.

Alternatively, the PPG sensor 320 may be transmissive-mode PPG sensor.For example, the PPG sensor 320 can be in a ring or “clothespin” formatwith the pressure sensor mounted below the photodetector 508. When theuser presses their finger or thumb inside the PPG sensor 320 ring ontoan external, hard surface, the finger deforms. The ring can be made outof a soft material to enable the proper transmission of the force andkeep the LED 512 preloaded onto the top of the finger.

FIGS. 14A and 14B are diagrams depicting example embodiments of sensingunits integrated into an encasing 520 of mobile devices 100. Theencasing 520 of the mobile device 100 is a sleeve designed to enclosethe mobile device 100. Cases are commonly used for mobile devices 100 toprotect the mobile device 100 from damage such as scratches. In thepresent disclosure, the encasing 520 is a separate sleeve for the mobiledevice 100 and includes the necessary components for the BP measurementsystem. The encasing 520 is designed to interface with the mobile device100 using a network communication device such as Bluetooth.

In FIG. 14A, a circular sensing unit 524 is shown. The circular sensingunit 524 includes a PPG sensor array 528 with multiple light emittingdiodes (LEDs) 512 and multiple of photodetectors 508. The PPG sensorarray 528 is coupled to a pressure array 532. Alternatively, a singleLED 512 may be employed, as exemplified in FIG. 14B. With the PPG sensorarray 528, the target artery 516 may be located and blood volumeoscillations from therein may be measured via selection of the largestamplitude waveform obtained from the photodetectors 508. The surface ofthe PPG sensor array 528, which constitutes the finger pressing area,may be circular with a 10 mm diameter or occupy a similar area with thesame or different shape, such as a rectangle 536, as shown in FIG. 14B.The 10 mm area facilitates the finger actuation in that a high enoughpressure can be easily achieved without being overly sensitive to thefinger forces. The PPG sensor array 528 surface may be flat or concaveto facilitate finger positioning on the PPG sensor array 528.

In another embodiment, a red, green, and blue (RGB) camera (e.g. frome-con Systems, USA) can be used as reflectance-mode PPG sensor array.The RGB camera can operate as multiple photodetectors and the cameraflash can operate as a light source. Each pixel in a RGB video providesblood volume waveforms at the three wavelengths. That is, the RGB videocan construct a “PPG image”. From the PPG image, “hot spots” in thefinger can be identified to measure the blood volume from the targetartery 516. The RBG camera, already built in the mobile device, may beleveraged to measure the blood volume oscillations.

FIG. 14A also depicts the PPG sensor array 528 as coupled to thepressure array 532. Various pressure or force sensors such as resistive,capacitive, or piezoelectric transducers may be included in the pressurearray 532 to measure the pressure applied 116 to the sensing unit 108.The specifications for the pressure sensor should be congruent with themeasurement of BP (e.g., a pressure range of 0 to 300 mmHg and aresolution of about 0.1 mmHg). As discussed above, the pressure sensormay be thin-filmed. In other embodiments, larger sensors such as loadcells could be accommodated in certain form factors. The pressure sensorarray 532 would typically be the same size as the PPG sensor array 528surface. A single pressure transducer may be employed or multiple,smaller pressure sensing elements could be used to ensure that thepressure is being uniformly applied via examination of the similarityamongst the forces exerted on each individual sensor. In other words,one of the benefits of using multiple pressure sensors, in any arrayform, is that the force applied to each individual pressure sensor canbe measured to determine whether the force is applied uniformly on thepressure sensors. That is, if the forces applied to each pressure sensorvary amongst one another, the force is not being applied uniformly. Theforce applied to each pressure sensor can be used to guide a user forsuccessful actuation of the sensor.

As shown in FIG. 14A, the circular sensing unit 524 is embedded on aback 540 of an encasing 520 for the mobile device 100. The encasing 520includes a processor 544, a battery 548, and an analog to digitalconverter 552. The encasing 520 may include a data acquisition system torecord measurements of BP in storage already included on the mobiledevice the encasing 520 holds. The system would include analog signalconditioning (including signal amplification and filtering with, e.g.,low and high cutoff frequencies of about 0.5 to at least 10 Hz) followedby analog-to-digital conversion at 552 (with, e.g., a sampling rate ofat least 25 Hz and a resolution of 12 bits or more). Alternative to theprocessor 544 a microcontroller may be included in the encasing 520. Themicrocontroller may include a Bluetooth transmission module, which maybe employed to send the digitized data wirelessly to the mobile device100 for display and processing. In other embodiments, any networkcommunication device may be used to receive and transmit digitized databetween the encasing 520 and the mobile device 100.

The entire “external” system may be battery powered by the battery 548.In form factors built into the mobile device, the digitized data may besent to the display 104 and stored in an available medium for processingin the mobile device 100. The storage medium, however, may be includedin the encasing 520. The necessary components could also be added on toor included in existing mobile devices 100 such as a cell phone, PDAs,laptops, tablets, wearables including smartwatches and wristbands, orany other form of a portable electronic device.

To compute BP or determine that the finger actuation was unsuccessful,the recorded data, stored in the storage medium, are analyzed by a setof algorithms implemented on the mobile device's processor 544.

The quality of the pressure applied 116 to the sensing unit 108, e.g.,in FIG. 9A, and blood volume waveform, e.g., in FIG. 9B, is initiallyassessed possibly after some filtering (e.g., bandpass filtering withcutoff frequencies of 0.5 to 10 Hz for the blood volume waveform). Ifthe pressure applied 116 to the sensing unit 108 does not cover a wideenough range (e.g., at least 50 mmHg) over a sufficiently long timeinterval (e.g., at least 10 seconds) or the shape of the blood volumepulses often do not show physiologic character (i.e., a rapid risefollowed by a slower decay), then the finger actuation may be deemedunsuccessful. In the event that multiple pressure sensors 532 areemployed, the finger actuation could also be deemed unsuccessful, if thepressure experienced by each sensor is significantly different, aspreviously described. Otherwise, the multiple pressures may be averagedto yield a single pressure applied 116 to the sensing unit 108.

If the pressure applied 116 to the sensing unit 108 and blood volumewaveform are considered to be of sufficient quality, the oscillogram 128is constructed, for example by the oscillogram generator 308 of FIG. 3,according to any method known in the art of cuff BP measurement. Forexample, the pressure applied 116 to the sensing unit 108 is lowpassfiltered or a polynomial is fitted to mitigate spurious fluctuations inthe pressure applied 116 to the sensing unit 108. The maximum andminimum of each beat of the blood volume waveform are detected. Theseextrema, as a function of the pressure applied 116 to the sensing unit108, are median filtered to attenuate respiratory and pulse ratevariability as well as artifact. Finally, the extrema are linearlyinterpolated, and the difference between the two envelopes is taken asthe oscillogram 128. If the oscillogram 128 does not exhibit physiologiccharacter (e.g., uni-modal and smooth), the finger actuation may also beconsidered unsuccessful. For a physiologic oscillogram, a parametricmodel (e.g., single or multiple Gaussian functions or a quadraticfunction) may be fitted to yield a more robust oscillogram.

Finger BP is next estimated from successful oscillograms according toknown algorithms in the art of oscillometry. For example, the basicmaximum oscillation algorithm, the standard fixed-ratio algorithm seenin FIGS. 6A and 6B, the fixed-slope algorithm, or some combination orvariant of the two may be employed. Alternatively, a patient-specificalgorithm seen in FIGS. 7A and 7B, which may be more accurate thanconventional population-based algorithms, may be applied. A third optionis a combination of simple and more sophisticated algorithms. Forexample, a combined algorithm could output a MP estimate via thepressure applied 116 at which the oscillogram 128 is maximal whenrelatively low quality oscillograms are obtained and all three BPestimates via the patient-specific algorithm when higher qualityoscillograms are measured. The algorithm could also output a confidencelevel on the accuracy of its BP estimates based on the measurementquality.

Standard brachial (arm) BP, which is the proven cardiovascular riskfactor, may also be derived. While finger and brachial MP and DP aresimilar, finger SP is higher than brachial SP due to arterial wavereflection. Brachial SP may be estimated by simple transformations offinger BP. For example, since the ratio of finger SP to brachial SP maydecrease with age, an age-dependent scaling of finger SP could beapplied to estimate brachial SP. Alternatively, a transfer function maybe applied to more accurately estimate brachial BP from finger BP. Thetransfer function would require input of the finger BP waveform, whichcould be obtained with the patient-specific algorithm. Anotherpossibility is to estimate brachial SP from finger DP and MP usingempirical formulas designed for brachial BP (e.g., MP=(⅓)*SP+(⅔)*DP).

Other physiologic parameters of interest such as pulse rate and pulserate variability may also be computed from the blood volume waveformusing any method known in the art. The pulse rate variability could beassessed to determine the presence of an arrhythmia such as atrialfibrillation using any method known in the art. If red and infrared PPGmeasurements are available, SpO2 may additionally be computed using anexisting method.

Finally, an algorithm could also be employed for early termination ofthe finger actuation. For example, the oscillogram 128 could beconstructed in real-time as the finger pressure is being applied. If theportion of the oscillogram that has been currently constructed issimilar to the same portion of a previously constructed, completeoscillogram, then the previous BP levels could reasonably be assumed andimmediately outputted. In this way, some BP measurements may only take afew seconds to make.

FIG. 14B is a diagram depicting a rectangular sensing unit 556. Therectangular sensing unit 556 includes a rectangular PPG sensor array 560with multiple photodetectors 508 and one LED 512 and a rectangularpressure sensor array 566. The rectangular sensing unit 556 is placed ona side 570 of the encasing 520, which may be better suited to the fingerpressing task.

FIG. 15 is a diagram depicting another embodiment of the cuff-less BPmeasurement system on the mobile device 100. For example, the mobiledevice 100 depicted in FIG. 15 is the same as the mobile device 100 ofFIG. 1. However, instead of using the encasing 520 to couple the sensingunit 108 to the mobile device 100, the existing PPG sensor or theexistingRGB camera 574 on the mobile device 100 is used. To complete thesensing unit, a donut shaped pressure sensor 578 is placed on top of andaround the PPG sensor 574 to allow the passage of light.

FIG. 16 is a diagram depicting another embodiment of the cuff-less BPmeasurement system. FIG. 16 depicts the cuff-less BP measurement systemwith an infrared PPG sensor 582 located below the display 104 of themobile device 100. The sensing unit 108, employing the infrared PPGsensor 582, could be placed under the display 104 while leveraging thepressure sensing capabilities of the display 104. In this case, apicture of the user's finger 586 could be displayed indicating exactlywhere the user should position their finger for subsequent pressing.

FIGS. 17A-17C are diagrams depicting an embodiment of the cuff-less BPmeasurement system with finger placement indicators. In FIG. 17A, thefinger placement indicator 590 facilitates the finger positioning on thesensing unit 108 of the mobile device 100. The finger placementindicator 590 is a physical barrier placed around the sensing unit 108to guide repeatable finger placement. The finger placement indicator 590may be included on the encasing 520 or as a separate item attached tothe mobile device 100 when using the RGB camera or PPG sensor of themobile device 100. The finger placement indicator 590 could beadjustable to accommodate different finger sizes or multiple fingerplacement indicators 590 could be offered for different finger sizes(i.e., small, medium, and large). The finger placement indicator couldalso be a more subtle physical barrier than that indicated 590.

In FIG. 17B, a visual guide finger placement indicator 594 is placed onthe mobile device 100. Alternatively, the visual guide finger placementindicator 594 may be on the encasing 520 of the mobile device 100. Forexample, lines could be drawn over the sensing unit 108 to guide theuser in placing the base of the finger nail between the LED 512 andphotodetector 508 and the center of the finger on the line passingthrough the LED 512 and photodetector 508, as also shown in FIG. 17C at594. In addition, the sensing unit 108 may be positioned so that aportion of the finger below the top knuckle can also rest on the deviceto ensure normal direction force application.

The cuff-less BP measurement system, in any of the embodiments, may alsobe accompanied by additional means to guide proper finger actuation. Inparticular, proper finger placement for a specific user may bedetermined via an initialization protocol. This protocol involvesmeasuring the oscillogram 128 at different finger positions on thesensing unit 108 and choosing the finger position based on theoscillogram amplitude and morphology (e.g., maximal oscillogram) orbased on an initial cuff BP reading.

FIGS. 18A-18D are diagrams depicting an example position detectionsystem included in the cuff-less BP measurement system. The camera thatis already built in the mobile device 100 may be leveraged to ensurethat the mobile device 100 is being held at heart level 600. The cameraof the mobile device 100, as discussed above with respect to the RGBcamera, may be used as a PPG sensor as well. For position detectionpurposes, the camera records an image of the face 604 while the mobiledevice 100 is known to be at heart level 600. For subsequent BPmeasurements, the camera records another image and compares the currentimage to the previously recorded image 604 known to be at heart level600. The silhouette from the current image should be close enough tothat of the previously recorded image. Otherwise, the application asksthe user to put the mobile device at heart level. An example image whenthe mobile device 100 is below heart level 600 is shown at 608. Thisapproach would only be effective when the user is in the uprightposture. The accelerometer that is already in the mobile device 100could also possibly be leveraged for confirming heart level 600.

In another embodiment, the cuff-less BP system may compensate for BPcalculations when it has been detected that the user had their BPmeasured without holding the mobile device 100 at heart level. Forexample, after instructing the user to hold the mobile device 100 atheart level and then proceed to steadily increase the applied fingerpressure, the system measures and records BP measurements. If the systemdetects that the mobile device 100 is not being held at heart level,then the recorded BP measurements can be adjusted accordingly for theheight at which the measurements were being taken using a rho-g-hcorrection, where rho is the known blood density, g is gravity, and h isthe vertical distance between the finger and heart estimated from theimages.

FIG. 19 is a flowchart depicting the example position detection systemincluded in the cuff-less BP measurement system. The system isinitialized at 204 and the pressure applied 116 by the finger isdetected at 208. To ensure that the user is holding the mobile device100 at heart level, the system captures a current photo 608 of the userat 700. The system then compares the current photo 608 to a previouslyrecorded or stored photo 604 of the user when the mobile device 100 isknown to be held at heart level at 704. If the current photo 608 is thesame as or similar enough to the previously recorded photo 604, then thesystem continues to measure and graph blood volume oscillations andpressure applied 116 to the sensing unit 108 with the finger at 224. If,however, the current photo 608 differs from the previously recordedphoto 604 by a predetermined amount, then the system provides feedbackto the user instructing to user to adjust the mobile device 100 to heartlevel at 712. In an embodiment, the photos that are captured may besilhouettes or outlines to be able to compare a size of the user todetermine if the mobile device 100 is at heart level.

As another example to guide proper finger actuation, a fingerprint couldbe taken and used to confirm and/or guide proper finger positioning onthe sensing unit 108 as well as to identify the user for a multi-userdevice. Maintaining an identity of users ensures measurements aretransmitted to the appropriate place. In addition, the application couldinclude an instructional video to explain how to use the devicecorrectly. Alternatively, the user could test for the best fingerposition by measuring the user's BP multiple times and recording thefinger position each time. After at least two attempts to measure theuser's BP, the application could determine which BP measurement resultsin the largest oscillogram and indicate to the user that the recordedfinger position for the largest oscillogram is the preferred fingerposition for that user.

In other embodiments, the mobile device 100 could act as the actuatorinstead of the user. For example, the mobile device 100 could include amotor driven system or a mechanical spring that would automaticallyapply the pressure to the finger placed on the sensing unit 108.Additionally, the method could also be integrated within non-mobiledevice form factors including elevator control panels, video gamecontrollers, doorbells, keychains, steering wheels, bathroom mirrors,pill bottle caps, etc.

Some portions of the above description present the techniques describedherein in terms of algorithms and symbolic representations of operationson information. These algorithmic descriptions and representations arethe means used by those skilled in the data processing arts to mosteffectively convey the substance of their work to others skilled in theart. These operations, while described functionally or logically, areunderstood to be implemented by computer programs. Furthermore, it hasalso proven convenient at times to refer to these arrangements ofoperations as modules or by functional names, without loss ofgenerality.

Unless specifically stated otherwise as apparent from the abovediscussion, it is appreciated that throughout the description,discussions utilizing terms such as “processing” or “computing” or“calculating” or “determining” or “displaying” or the like, refer to theaction and processes of a computer system, or similar electroniccomputing device, that manipulates and transforms data represented asphysical (electronic) quantities within the computer system memories orregisters or other such information storage, transmission or displaydevices.

Certain aspects of the described techniques include process steps andinstructions described herein in the form of an algorithm. It should benoted that the described process steps and instructions could beembodied in software, firmware or hardware, and when embodied insoftware, could be downloaded to reside on and be operated fromdifferent platforms used by real time network operating systems.

The present disclosure also relates to an apparatus for performing theoperations herein. This apparatus may be specially constructed for therequired purposes, or it may comprise a computer selectively activatedor reconfigured by a computer program stored on a computer readablemedium that can be accessed by the computer. Such a computer program maybe stored in a tangible computer readable storage medium, such as, butis not limited to, any type of disk including floppy disks, opticaldisks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs),random access memories (RAMs), EPROMs, EEPROMs, magnetic or opticalcards, application specific integrated circuits (ASICs), or any type ofmedia suitable for storing electronic instructions, and each coupled toa computer system bus. Furthermore, the computers referred to in thespecification may include a single processor or may be architecturesemploying multiple processor designs for increased computing capability.

The algorithms and operations presented herein are not inherentlyrelated to any particular computer or other apparatus. Variousgeneral-purpose systems may also be used with programs in accordancewith the teachings herein, or it may prove convenient to construct morespecialized apparatuses to perform the required method steps. Therequired structure for a variety of these systems will be apparent tothose of skill in the art, along with equivalent variations. Inaddition, the present disclosure is not described with reference to anyparticular programming language. It is appreciated that a variety ofprogramming languages may be used to implement the teachings of thepresent disclosure as described herein.

The foregoing description of the embodiments has been provided forpurposes of illustration and description. It is not intended to beexhaustive or to limit the disclosure. Individual elements or featuresof a particular embodiment are generally not limited to that particularembodiment, but, where applicable, are interchangeable and can be usedin a selected embodiment, even if not specifically shown or described.The same may also be varied in many ways. Such variations are not to beregarded as a departure from the disclosure, and all such modificationsare intended to be included within the scope of the disclosure.

1.-20. (canceled)
 21. A mobile device, comprising: a housing definingtwo opposing exterior surfaces, each of the opposing exterior surfacesbeing substantially planar; a processor enclosed within the housing; adisplay unit integrated into a first of the two opposing exteriorsurfaces; a reflectance-mode photoplethysmography (PPG) sensorintegrated into the housing and configured to measure blood volumeoscillations; a force sensor disposed underneath the display unit andconfigured to measure applied pressure; a visual guide on the displayunit, such that the visual guide is an indicia for placement of thefingertip on the device; and a non-transitory computer-readable mediumenclosed in the housing that stores instructions that, when executed bythe processor, cause the processor to: measure pressure applied to thesensing unit by a fingertip of a user, measure blood volume oscillationsin the fingertip, guide the user via the display unit to vary pressurebeing applied to the sensing unit while the blood volume oscillationsand pressure are measured, generate an oscillogram from the measuredpressure and the measured blood volume oscillations, where theoscillogram plots amplitude of blood volume oscillations as a functionof the measured pressure, calculate a blood pressure value from theoscillogram, and present the blood pressure value on the display unit.22. The mobile device of claim 21 wherein the PPG sensor is furtherdefined as a camera.
 23. The mobile device of claim 21 includesinstructions that, when executed by the processor, cause the processorto guide the user to hold the device at a height aligned with the heartof the user.
 24. The mobile device of claim 23 further includesinstructions that, when executed by the processor, cause the processorto capture an image of the user with a camera, compare the capturedimage to a reference image of the user, and instruct the user to holdthe mobile device at a height aligned with the heart of the user basedon the comparison of the captured image with the reference image, wherethe reference image was captured when the device was being held at aheight aligned with the heart of the user.
 25. The mobile device ofclaim 21 further includes instructions that, when executed by theprocessor, cause the processor to capture an image of the user with acamera, compare the captured image to a reference image of the user,detect the height at which the device is being held relative to theheart based on the comparison of the captured image with the referenceimage, where the reference image was captured when the device was beingheld at a height aligned with the heart of the user, and compensate thecalculated blood pressure value in accordance with the detected height.26. The mobile device of claim 21 wherein the processor generates ablood pressure value by representing the oscillogram with a mathematicalmodel, wherein the mathematical model is defined in terms of parameterswith unknown values, the parameters indicating finger systolic pressureand finger diastolic pressure and specifying a nonlinear bloodvolume-transmural pressure relationship of the fingertip artery;estimating the parameters of the mathematical model by fitting themathematical model to the oscillogram; and computing brachial systolicpressure and diastolic pressure using the parameter estimates.
 27. Themobile device of claim 26 wherein computing brachial systolic pressureand diastolic pressure further comprises use of a transfer function. 28.A mobile device, comprising: a housing defining two opposing exteriorsurfaces, each of the opposing exterior surfaces being substantiallyplanar; a processor enclosed within the housing; a display unitintegrated into a first of the two opposing exterior surfaces; areflectance-mode photoplethysmography (PPG) sensor integrated into thehousing and configured to measure blood volume oscillations; a forcesensor disposed underneath the display unit and configured to measureapplied pressure; a visual guide on the display unit and arranged inrelation to the PPG sensor, where the visual guide comprises indicia toguide a user in placing base of fingernail and center of finger inrelation to the PPG sensor; and a non-transitory computer-readablemedium enclosed in the housing that stores instructions that, whenexecuted by the processor, cause the processor to: measure pressureapplied to the sensing unit by a fingertip of a user, measure bloodvolume oscillations in the fingertip, guide the user via the displayunit to vary pressure being applied to the sensing unit while the bloodvolume oscillations and pressure are measured, generate an oscillogramfrom the measured pressure and the measured blood volume oscillations,where the oscillogram plots amplitude of blood volume oscillations as afunction of the measured pressure, calculate a blood pressure value fromthe oscillogram, and present the blood pressure value on the displayunit.
 29. The mobile device of claim 28 wherein the PPG sensor isfurther defined as a camera.
 30. The mobile device of claim 28 includesinstructions that, when executed by the processor, cause the processorto guide the user to hold the device at a height aligned with the heartof the user.
 31. The mobile device of claim 30 further includesinstructions that, when executed by the processor, cause the processorto capture an image of the user with a camera, compare the capturedimage to a reference image of the user, and instruct the user to holdthe mobile device at a height aligned with the heart of the user basedon the comparison of the captured image with the reference image, wherethe reference image was captured when the device was being held at aheight aligned with the heart of the user.
 32. The mobile device ofclaim 28 further includes instructions that, when executed by theprocessor, cause the processor to capture an image of the user with acamera, compare the captured image to a reference image of the user,detect the height at which the device is being held relative to theheart based on the comparison of the captured image with the referenceimage, where the reference image was captured when the device was beingheld at a height aligned with the heart of the user, and compensate thecalculated blood pressure value in accordance with the detected height.33. The mobile device of claim 28 wherein the processor generates ablood pressure value by representing the oscillogram with a mathematicalmodel, wherein the mathematical model is defined in terms of parameterswith unknown values, the parameters indicating finger systolic pressureand finger diastolic pressure and specifying a nonlinear bloodvolume-transmural pressure relationship of the fingertip artery;estimating the parameters of the mathematical model by fitting themathematical model to the oscillogram; and computing brachial systolicpressure and diastolic pressure using the parameter estimates.
 34. Themobile device of claim 33 wherein computing brachial systolic pressureand diastolic pressure further comprises use of a transfer function. 35.A mobile device, comprising: a housing defining two opposing exteriorsurfaces, each of the opposing exterior surfaces being substantiallyplanar; a processor enclosed within the housing; a display unitintegrated into a first of the two opposing exterior surfaces; areflectance-mode photoplethysmography (PPG) sensor integrated into thehousing and configured to measure blood volume oscillations; a forcesensor disposed underneath the display unit and configured to measureapplied pressure; a visual guide on the display unit and arranged inrelation to the PPG sensor, wherein the visual guide comprises indiciato guide a user in placing a surface of the fingertip on opposite sideof the finger from a fingernail on the finger and distal from the distalinterphalangeal joint of the finger onto the PPG sensor; and anon-transitory computer-readable medium enclosed in the housing thatstores instructions that, when executed by the processor, cause theprocessor to: measure pressure applied to the sensing unit by afingertip of a user, measure blood volume oscillations in the fingertip,guide the user via the display unit to vary pressure being applied tothe sensing unit while the blood volume oscillations and pressure aremeasured, generate an oscillogram from the measured pressure and themeasured blood volume oscillations, where the oscillogram plotsamplitude of blood volume oscillations as a function of the measuredpressure, calculate a blood pressure value from the oscillogram, andpresent the blood pressure value on the display unit.
 36. The mobiledevice of claim 35 wherein the PPG sensor is further defined as acamera.
 37. The mobile device of claim 35 includes instructions that,when executed by the processor, cause the processor to guide the user tohold the device at a height aligned with the heart of the user.
 38. Themobile device of claim 37 further includes instructions that, whenexecuted by the processor, cause the processor to capture an image ofthe user with a camera, compare the captured image to a reference imageof the user, and instruct the user to hold the mobile device at a heightaligned with the heart of the user based on the comparison of thecaptured image with the reference image, where the reference image wascaptured when the device was being held at a height aligned with theheart of the user.
 39. The mobile device of claim 35 further includesinstructions that, when executed by the processor, cause the processorto capture an image of the user with a camera, compare the capturedimage to a reference image of the user, detect the height at which thedevice is being held relative to the heart based on the comparison ofthe captured image with the reference image, where the reference imagewas captured when the device was being held at a height aligned with theheart of the user, and compensate the calculated blood pressure value inaccordance with the detected height.
 40. The mobile device of claim 35wherein the processor generates a blood pressure value by representingthe oscillogram with a mathematical model, wherein the mathematicalmodel is defined in terms of parameters with unknown values, theparameters indicating finger systolic pressure and finger diastolicpressure and specifying a nonlinear blood volume-transmural pressurerelationship of the fingertip artery; estimating the parameters of themathematical model by fitting the mathematical model to the oscillogram;and computing brachial systolic pressure and diastolic pressure usingthe parameter estimates.
 41. The mobile device of claim 40 whereincomputing brachial systolic pressure and diastolic pressure furthercomprises use of a transfer function.